• Journal of Mechanical Science and Technology
• /
• v.19 no.spc1
• /
• pp.452-460
• /
• 2005

Based on an introduced optimal trajectory planning method, this paper mainly deals with the accuracy analysis during the function approximation process of the optimal trajectory planning method. The basis functions are composed of Hermit polynomials and Fourier series to improve the approximation accuracy. Since the approximation accuracy is affected by the given orders of each basis function, the accuracy of the optimal solution is examined by changing the combinations of the orders of Hermit polynomials and Fourier series as the approximation basis functions. As a result, it is found that the proper approximation basis functions are the $5^{th}$ order Hermit polynomials and the $7^{th}-10^{th}$ order of Fourier series.

• Journal of the Korean Statistical Society
• /
• v.27 no.1
• /
• pp.57-66
• /
• 1998

In the analysis of time series it is an important issue to determine whether a time series under study is stationary. For the test of the stationary of the time series the Dickey-Fuller (DF) type tests have been mainly used. In this paper, we consider the regular unit root tests and seasonal unit root tests based on the generalized Durbin-Watson (DW) statistics when the errors are independent. The limiting distributions of the proposed DW-type test statistics are the functionals of standard Brownian motions. We also obtain the finite distributions and powers of the DW-type test statistics and compare the performances with the DF-type tests. It is observed that the DW-type test statistics have good behaviors against the DF-type test statistics especially in the nonzero (seasonal) mean model.

• Korean Journal of Hydrosciences
• /
• v.8
• /
• pp.125-136
• /
• 1997

The simulation techniques of hydrologic data series have develped for the purposes of the design of water resources system, the optimization of reservoir operation, and the design of flood control of reservoir, etc. While the stochastic models are usually used in most analysis of water resources fields for the generation of data sequences, the indexed sequential modeling (ISM) method based on generation of a series of overlapping short-term flow sequences directly from the historical record has been used for the data generation in the western USA since the early of 1980s. It was reported that the reliable results by ISM were obtained in practical applications. In this study, we generate annual inflow series at a location of Hong Cheon Dam site by using ISM method and autoregressive, order-1 model (AR(1)), and estimate the drought characteristics for the comparison aim between ISM and AR(1).

• The Korean Journal of Applied Statistics
• /
• v.1 no.1
• /
• pp.57-67
• /
• 1987

In time series analysis, we usually require the assumption that time series are stationary. But we may often encounter time series whose parameter values subject to change. Inthis paper w propose a method which can detect the variance change point in anAR(1) model which is subjct to changesat non-predictable time points. Proposed method is compared with other methods using the simulated and real data.

• Journal of Integrative Natural Science
• /
• v.1 no.2
• /
• pp.76-78
• /
• 2008

A series of the long-chain iron(II) alkylsulfonate hydrates were synthesized via self-assembly of surfactant alkyl chains in aqueous medium. Reaction of iron(II) salts with n-alkylsulfonate yields lamellar $Fe(CnH2n+1SO3)2{\cdot}4H_2O$. These compounds show a layered structure, as determined by XRD, consisting of alternating organic alkylsulfonate layers and inorganic iron(II) hydrate layers, with interlayer distances of upto 3.2 nm. This lamellar structure may be attributed to the amphiphilic nature of the surfactants, mediating the coordination and H-bionding interactions, and the hydrophobic alkyl chains. An alkyl chain packing of present system are differ from those of similar Cu(II) series, which are attributed from the size of hydrated metal(II) ions.

• Bulletin of the Society of Naval Architects of Korea
• /
• v.27 no.1
• /
• pp.84-98
• /
• 1990

Fifteen(l5) series hull forms for full slow-speed ships were prepared by expanding the basic parent hull form developed through the extensive theoretical and experimental studies, and model tests were carried out for each of the series hull forms. A set of systematic data was prepared from the test results and utilized to derive regression equations for the prediction of resistance and powering characteristics by statistical analysis. Computer program has been prepared based on the results of analysis and a sample run is presented.

• 유공압시스템학회:학술대회논문집
• /
• 2010.06a
• /
• pp.49-55
• /
• 2010

A series hydraulic hybrid vehicle(SHHV) concept has been explored as a potential pathway to an ultra-efficient city vehicle. Improvements in SHHV fuel economy with reduced emissions strongly depend on their supervisory control strategy. Thermostatic control is simple and reliable but it's cause of frequent engine on-off. Therefore, power follower strategy is presented. In this paper, thermostatic control strategy and power follower strategy is compared for the SHHV model developed using AMESim.

• Proceedings of the KIEE Conference
• /
• 2000.07d
• /
• pp.2968-2970
• /
• 2000

시계열(time series)이란 한 사상 또는 여러 사상에 대하여 시간의 흐름에 따라 일정한 간격으로 이들을 관측하여 기록한 자료를 말한다. 이러한 시계열은 어떠한 경제현상이나 자연현상에 관한 시간적 변화를 나타내는 역사적 계열(historical series)이므로 어느 한 시점에서 관측된 시계열자료는 그 이전까지의 자료들에 주로 의존하게 된다. 따라서 시계열분석을 통한 예측에서는 과거의 자료들을 분석하여 법칙성을 발견해서 이를 모형화하여 추정하고. 이 추정된 모형을 사용하여 미래에 관측될 값들을 예측하게 된다. 본 연구에서는 ARMA (p, q)모형 (autoregressive moving-average model)을 이용하여 시계열 데이터를 분석하며 계수의 추정에는 Levinson-Durbin 알고리듬과 Newton-Raphson Method를 이용한다.

• Proceedings of the KIEE Conference
• /
• 1995.07b
• /
• pp.578-580
• /
• 1995

In this paper, a method for the daily maximum load forecasting which uses a chaotic time series in power system and artificial neural network. We find the characteristics of chaos in power load curve and then determine a optimal embedding dimension and delay time, For the load forecast of one day ahead daily maximum power, we use the time series load data obtained in previous year. By using of embedding dimension and delay time, we construct a strange attractor in pseudo phase plane and the artificial neural network model trained with the attractor font mentioned above. The one day ahead forecast errors are about 1.4% of absolute percentage average error.

• Journal of Applied Reliability
• /
• v.1 no.1
• /
• pp.1-8
• /
• 2001

Redundancy allocation problems have been considered at single-level systems and it may be the best policy in some specific situations, but not in general. With regards to reliability, it is most effective to allocate the lowest objects, because parallel-series systems are more reliable than series-parallel systems. However, the smaller and lower in the system an object is, the more time and accuracy are needed for duplicating it, and so, the cost can be decreased by using modular redundancy Therefore, providing redundancy at high levels like as modules or subsystems, can be more economical than providing redundancy at low levels or duplicating components. In this paper, the problem in which redundancy is allocated at all level in a series system is addressed, a mixed integer nonlinear programming model is presented and a genetic algorithm is proposed. An example illustrates the procedure.